Traditional capacity planning is limited in that it is system oriented. The task typically has been approached as a way to determine the overall resource amount that is required by a server to meet an expected demand. After determining the resource amount, the amount of each resource required by a future time is predicted using a variety of modeling techniques.
Traditional capacity planning techniques have disadvantages because they are not accurate. In particular, modern transactional systems incur different load levels over time for a variety of reasons. The system load may include transaction types which incur different capacity demands on the system. Thus, previous capacity planning techniques may not accurately account for all factors that affect resource usage when determining the amount of a resource required as a direct result of one or more transactions. For example, users purchasing a product may require much more system capacity than a user browsing a catalog. Furthermore, key predictive inputs, such as new marketing campaigns, are rarely measured in terms of overall server usage. Predicting capacity planning as accurately as possible for a network application or server is valuable.